Right Hire

We are looking for a passionate and skilled backend developer with strong expertise in .NET Core to join our engineering team at LeadSquared. This role is ideal for someone who thrives in building scalable, high performance services and is open to transitioning into Java-based technologies in the future. You will be responsible for designing and developing robust backend systems, APIs, and services that power our platform. A strong sense of ownership, attention to detail, and a commitment to writing clean, maintainable code are essential qualities we look for.

KEY RESPONSIBILITIES

▪️ Design, develop, and maintain scalable backend services using .NET Core.

▪️ Build and optimize RESTful APIs and microservices.

▪️ Collaborate with cross-functional teams to define, design, and ship new features. ▪️ Write clean, efficient, and testable code with a focus on long-term maintainability.

▪️ Optimize database queries and ensure high performance for data-intensive operations.

▪️ Implement caching and messaging solutions for performance and reliability. ▪️ Participate in code reviews and contribute to engineering best practices.

REQUIRED SKILLS & QUALIFICATIONS

▪️ 3–5 years of hands-on experience in backend development with .NET Core.

▪️ Strong programming skills in C#.

▪️ Experience with ASP.NET Core MVC, Web API, and WCF.

▪️ Solid understanding of multi-threading, asynchronous programming, and concurrency.

▪️ Experience with MySQL, SQL Server, or equivalent relational databases.

▪️ Strong expertise in SQL programming and query optimization for large datasets.

▪️ Familiarity with caching solutions such as Redis.

▪️ Experience with message brokers such as RabbitMQ, Kafka, or AWS SQS.

▪️ Hands-on experience with cloud platforms — preferably AWS, or Azure/GCP.

▪️ Exposure to analytics, observability, monitoring, and performance tuning.

▪️ Strong foundation in software design principles and logical thinking. Good to Have

▪️ Familiarity with containerization tools — Docker and Kubernetes.

▪️ Understanding of CI/CD pipelines and DevOps practices.

About the Role

LeadSquared is looking for a Backend Heavy Engineer with strong expertise in Java backend development and hands-on experience working with chatbots / conversational systems.

The ideal candidate should have a strong foundation in backend engineering, distributed systems and API development, along with exposure to building or integrating chatbot, conversational AI or messaging-based solutions.

Key Responsibilities

• Design, develop and maintain scalable backend services and APIs using Java.
• Build high-performance, reliable and secure microservices-based applications.
• Develop and integrate chatbot / conversational platforms with backend systems.
• Work on chatbot workflows, conversation flows, APIs, integrations and business logic.
• Integrate backend services with LLM/AI-powered conversational systems, where required.
• Build RESTful APIs and integrations with internal and third-party platforms.
• Work with databases, caching, queues and distributed systems to support scalable applications.
• Troubleshoot performance, reliability and production issues.
• Collaborate with Product, AI/ML, Frontend and Engineering teams to deliver end-to-end solutions.
• Participate in architecture discussions, code reviews and technical design.
• Write clean, maintainable and well-tested production-grade code.

Must-Have Skills

• 4–6 years of strong backend development experience.
• Strong hands-on experience with Java, Spring Boot and REST APIs.
• Good understanding of Microservices architecture.
• Experience with SQL databases such as MySQL/PostgreSQL.
• Good understanding of data structures, algorithms and object-oriented programming.
• Hands-on experience with chatbots, conversational applications, chatbot frameworks or messaging platforms.
• Experience integrating chatbot systems with backend APIs/services.
• Understanding of asynchronous processing, queues and event-driven architecture.
• Good understanding of Git, CI/CD and production deployment practices.

Good to Have

• Experience with Generative AI / LLM-based chatbots.
• Exposure to RAG, embeddings, prompt engineering or LLM APIs.
• Experience with Kafka, Redis, Elasticsearch or similar technologies.
• Cloud experience with AWS/Azure/GCP.
• Experience with Docker/Kubernetes.
• Experience building customer-facing SaaS products.
• Exposure to CRM, MarTech, SalesTech or enterprise platforms.

Ideal Candidate

We are looking for someone who is backend-first and Java-heavy, but has also worked on chatbot/conversational use cases. The candidate should be comfortable owning backend services end-to-end and collaborating with AI/ML teams to build scalable conversational experiences.

Ideal profile:

Java + Spring Boot + Microservices + Strong Backend Engineering + Chatbot/Conversational AI Experience.

About the Role

LeadSquared is looking for a Senior AI/ML Engineer who brings a strong combination of traditional Machine Learning expertise and hands-on experience building Agentic AI systems.

The ideal candidate will be responsible for designing, developing, and deploying intelligent AI/ML solutions that power LeadSquared's products, while also building the next generation of LLM-powered agents, AI workflows, and autonomous decision-making systems.

This role requires someone who can go beyond experimentation and take AI solutions from problem definition → model development → production deployment → monitoring and continuous improvement.

Key Responsibilities

• Design, develop and deploy ML models for real-world business and product use cases.
• Work on LLMs, Generative AI and Agentic AI applications.
• Build AI agents capable of reasoning, planning, tool calling and multi-step task execution.
• Develop RAG pipelines, embeddings, vector search and knowledge-based AI systems.
• Design agent workflows involving function/tool calling, memory, context management and orchestration.
• Build and evaluate multi-agent systems where applicable.
• Apply traditional ML techniques including classification, regression, ranking, recommendation, NLP and predictive modelling.
• Fine-tune and optimize LLMs/models for specific business use cases.
• Develop robust evaluation frameworks for LLM and agent performance, accuracy, hallucination, latency and cost.
• Productionize AI/ML models and integrate them with scalable product architectures.
• Work closely with Product, Engineering, Data Science and Business teams to identify and solve high-impact problems.
• Optimize AI systems for performance, scalability, reliability and cost efficiency.
• Establish best practices around MLOps, model monitoring, experimentation and continuous improvement.

Must-Have Skills

• Strong programming experience in Python.
• Strong fundamentals in Machine Learning, Deep Learning, NLP and Statistics.
• Hands-on experience with LLMs and Generative AI.
• Strong understanding of RAG, embeddings, vector databases and semantic search.
• Experience with Agentic AI / AI Agents, including tool calling and workflow orchestration.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI or equivalent.
• Experience working with models/APIs such as OpenAI, Anthropic, Gemini, Llama or equivalent.
• Experience with PyTorch/TensorFlow and ML libraries such as Scikit-learn.
• Good understanding of REST APIs, microservices and cloud platforms.
• Experience taking AI/ML solutions into production environments.

Good to Have

• Experience building multi-agent architectures.
• Experience with AI evaluation, observability and guardrails.
• Experience with fine-tuning, LoRA/PEFT or model optimization.
• Knowledge of MLOps/LLMOps.
• Experience with AWS/Azure/GCP.
• Experience with Kafka, Redis, Docker/Kubernetes or similar technologies.
• Experience in SaaS, CRM, MarTech, SalesTech or enterprise applications.

What We Are Looking For

We are looking for a builder, not someone who has worked only on AI POCs or research projects. The candidate should demonstrate the ability to combine strong ML fundamentals with modern Agentic AI capabilities and build reliable, production-grade AI solutions.

Ideal profile:

Traditional ML + GenAI/LLM + Agentic AI + Production Engineering + Strong Product Mindset.

Full-Stack Engineer (Backend Heavy)

Experience: 4–6 Years | Function: Engineering — Product | Location: On-site

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a Full-Stack Engineer with a strong backend bias to help build end-to-end product experiences across Lumen and Agent Studio. You will own features from database and API design through to the front-end experience, working closely with product and design to ship AI-powered experiences that real business users depend on every day.

What You’ll Do

Design and build backend services and APIs in Python that power core product and AI-agent features.

Build front-end interfaces and experiences that let users interact naturally with AI agents, insights and CRM workflows.

Own features end-to-end — from data modeling and backend logic to UI implementation, testing and release.

Work with product managers and designers to translate requirements into well-architected, scalable systems.

Integrate with LLM-based and agentic backend systems built by the AI/ML engineering team.

Optimize application performance, reliability and code quality across the stack.

Engage directly with customers and customer success teams to understand workflows, triage issues and inform roadmap decisions.

What We’re Looking For

4–6 years of professional full-stack engineering experience, with a clear backend-heavy skill set in Python.

Strong experience designing and building REST/GraphQL APIs, data models and scalable backend services.

Working proficiency with modern front-end frameworks (e.g., React) to build and integrate user-facing features.

Experience with relational/NoSQL databases, caching and cloud infrastructure.

Ability to move fast in a zero-to-one environment while maintaining code quality and system reliability.

Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

Experience building features on top of LLM or AI-agent backends.

Prior experience in CRM, SaaS or enterprise business applications.

Exposure to real-time or voice-based product interfaces.

About Us

Invorto is our Voice AI product, bringing intelligent voice agents to real-world customer and operational use cases. Our voice pipeline is built in Python, running an STT → LLM → TTS architecture on top of the Pipecat framework.

This is a chance to work on hard problems in voice AI — latency, accuracy, naturalness, and reliability — building zero-to-one, owning your area end-to-end, and shipping to production at scale.

Note: This is a customer-facing role, and strong communication skills are essential.

About the Role

We're looking for a Voice AI Research Engineer to join the Invorto team and help build and continuously improve the voice AI systems that power our intelligent voice agents. This role is focused on the specialized craft of voice AI — designing evaluation and automation frameworks that ensure our STT, LLM, and TTS pipeline performs reliably in real-world, production conditions.

What You'll Do

• Design and build automated testing and quality frameworks for our STT → LLM → TTS voice pipeline, built on Pipecat
• Evaluate and benchmark STT, LLM, and TTS/ASR components on accuracy, latency, naturalness, and robustness across accents, languages, and real-world audio conditions
• Work hands-on with STT, TTS, and ASR models — fine-tuning, evaluating, and improving them for production use cases
• Identify failure modes and edge cases across the pipeline (background noise, accents, interruptions, turn-taking, latency, pipeline-stage handoffs) and build systems to catch them before production
• Collaborate closely with engineering to integrate quality checks and automation into the voice agent development lifecycle within the Pipecat-based architecture
• Research and stay current with advances in voice AI, and bring in new techniques, models, and tools to improve pipeline performance
• Work directly with customers to understand real-world voice use cases and translate them into evaluation criteria and quality benchmarks
• Partner with product and engineering to define what "production-grade quality" means for voice agents and drive the team toward it

What We're Looking For

• 4–6 years of experience, with a specialization in voice AI systems and automated quality evaluation
• Hands-on experience with STT (Speech-to-Text), TTS (Text-to-Speech), and ASR (Automatic Speech Recognition) models
• Experience designing and building automated testing/evaluation frameworks for voice or speech systems
• Strong understanding of what drives voice AI quality — accuracy, latency, naturalness, and robustness to real-world variability
• Strong programming skills in Python; familiarity with Pipecat or similar voice pipeline/orchestration frameworks is a plus
• Understanding of STT → LLM → TTS pipeline architectures and the trade-offs involved at each stage
• Research mindset — comfortable exploring new models, techniques, and tools and translating them into practical improvements
• Excellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and validate quality expectations

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a QA Engineer who specializes in testing agentic AI platforms. You will design and automate quality processes for systems that involve LLMs, autonomous agents, tool use and orchestration across Lumen and Agent Studio — ensuring that AI-driven workflows behave reliably, safely and predictably in production, not just in a demo.

What You’ll Do

• Design and build automated test suites and evaluation frameworks for agentic AI workflows, including multi-step and tool-calling behaviors.
• Use AI/LLM-based QA tools and evaluation frameworks to test model outputs, agent decisions and end-to-end task completion at scale.
• Define quality metrics and benchmarks for agent reliability, correctness, latency and safety, and track them over releases.
• Identify edge cases, failure modes and regressions specific to non-deterministic AI systems, and build automated checks to catch them early.
• Integrate automated agent/LLM testing into CI/CD pipelines to support fast, reliable iteration.
• Partner closely with AI/ML and backend engineers to reproduce issues, root-cause failures and validate fixes.
• Work with customers and customer-facing teams to understand real-world usage patterns and translate them into test scenarios.

What We’re Looking For

• 2–4 years of QA/test automation experience, including hands-on work testing agentic AI or LLM-based platforms.
• Practical experience using AI-focused QA/evaluation tools to test agent behavior, prompts and model outputs.
• Strong scripting/automation skills (Python preferred) to build and maintain test frameworks.
• Understanding of how LLM-based agents work — tool calling, orchestration, memory, reasoning chains — well enough to design meaningful test cases.
• Comfort working with non-deterministic systems and designing evaluation approaches beyond traditional pass/fail testing.
• Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

• Experience testing voice AI or real-time conversational systems.
• Familiarity with CRM or enterprise SaaS platforms.
• Exposure to enterprise security or compliance testing for AI systems.

We're looking for a seasoned sales professional with experience driving enterprise SaaS/technology sales, managing complex sales cycles, and closing large-value deals. This is a high-impact individual contributor role focused on new business acquisition, strategic account growth, and building relationships with senior stakeholders.

Key requirements:

* 15+ years of Enterprise SaaS/Technology Sales experience

* Proven track record of selling B2B SaaS solutions to mid-market and enterprise customers

* Success in closing large enterprise deals and consistently exceeding revenue targets

* Experience engaging with CXO-level stakeholders and influencing decision-makers

* Strong consultative selling, solution selling, and account management capabilities

* Ability to manage complex sales cycles involving multiple stakeholders

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